Two broad aims drive weed science research: improved management and improvedunderstanding of weed biology and ecology. In recent years, agriculturalweed research addressing these two aims has effectively split into separatesubdisciplines despite repeated calls for greater integration. Although someexcellent work is being done, agricultural weed research has developed avery high level of repetitiveness, a preponderance of purely descriptivestudies, and has failed to clearly articulate novel hypotheses linked toestablished bodies of ecological and evolutionary theory. In contrast,invasive plant research attracts a diverse cadre of nonweed scientists usinginvasions to explore broader and more integrated biological questionsgrounded in theory. We propose that although studies focused on weedmanagement remain vitally important, agricultural weed research wouldbenefit from deeper theoretical justification, a broader vision, andincreased collaboration across diverse disciplines. To initiate change inthis direction, we call for more emphasis on interdisciplinary training forweed scientists, and for focused workshops and working groups to developspecific areas of research and promote interactions among weed scientistsand with the wider scientific community.

In this paper, we consider a single-server queue with stationary input, where each job joining the queue has an associated deadline. The deadline is a time constraint on job sojourn time and may be finite or infinite. If the job does not complete service before its deadline expires, it abandons the queue and the partial service it may have received up to that point is wasted. When the queue operates under a first-come-first served discipline, we establish conditions under which the actual workload process—that is, the work the server eventually processes—is unstable, weakly stable, and strongly stable. An interesting phenomenon observed is that in a nontrivial portion of the parameter space, the queue is weakly stable, but not strongly stable. We also indicate how our results apply to other nonidling service disciplines. We finally extend the results for a single node to acyclic (feed-forward) networks of queues with either per-queue or network-wide deadlines.